At IAS, we are always looking at ways to not only enhance technologies for our customers, but also widen the understanding of the latest developments in digital advertising. To help you stay up to date on the latest innovation, we bring you Quick Bytes: Ad Fraud.
Increased adoption and innovation pushes platforms forward, but also creates challenges around ad fraud. Ad fraud costs advertisers billions of dollars. Fraudsters follow the ad spend, especially in new environments that may lack standards and advanced measurement.
There are many types of ad fraud where bots are used to prevent delivery of ads to real people. Fraudsters are becoming more sophisticated, using Artificial Intelligence (AI) and Machine Learning (ML) techniques to perpetrate fraud. They’re programmed to appear as human as possible – and as a result, more accurate and sophisticated tools for detection are needed.
IAS takes a unique approach to combat ad fraud and ensure ads are seen by real people. We combine extensive data analysis, sophisticated machine learning techniques, and reverse-engineer malicious code. And with the IAS Threat Lab, our elite bot-catching team, we uncover even the most sophisticated bots.
Our latest Media Quality Report shows the major difference robust defenses can make in fending off fraudsters. It showed that global ad fraud rates for optimized campaigns were 1% or below across all ad environments, landing between 0.3% and 1%. In fact, advertising campaigns that did not incorporate a form of fraud mitigation strategy encountered levels of ad fraud up to 13x higher worldwide than those that did.
IAS is committed to remaining on the forefront of this new technological revolution and to making sure that our customers and the industry remains educated about the potential of these technologies to fight ad fraud and help marketers not lose out to wasted ad spend.
Discover how IAS’s leading ad fraud detection and prevention protects premium publishers from ad fraud and saves the world’s top advertisers’ ad spend from being wasted.
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